Solution spinning of cellulose carbon nanotube composites using room temperature ionic liquids

Multiwall carbon nanotube (MWCNT)/cellulose composite fibers were processed from solutions in ethyl methylimidazolium acetate (EMIAc). Rheological percolation in MWCNT/Cellulose/EMIAc solution was observed above 0.01 mass fraction of MWCNT, while electrical percolation in oriented fibers was observed above 0.05 mass fraction of MWCNTs with respect to the weight of the cellulose. Cellulose orientation and crystal size were significantly higher in the composite than in the control cellulose fiber. In addition, in the composite fiber, carbon nanotube orientation was higher than cellulose orientation. At 0.05 mass fraction MWCNT, fiber tensile strength increased by about 25%, strain to failure increased by 100%, and modulus essentially remained unchanged. The composite fibers showed lower thermal shrinkage than the control cellulose fiber. The axial electrical conductivity at 0.1 mass fraction MWCNTs in these oriented fibers was more than 3000 S/m.     

Photopolymerization and thermal behavior of phosphate diacrylate and triacrylate used as reactive‐type flame‐retardant monomers in ultraviolet‐curable resins

Tri(acryloyloxyethyl)phosphate (TAEP) and di(acryloyloxyethyl)ethyl phosphate (DAEEP) were used as reactive‐type flame‐retardant monomers along with commercial epoxy acrylate and polyurethane acrylate oligomers in ultraviolet (UV)‐curable resins. The concentrations of the monomers were varied from 17 to 50 wt %. The addition of the monomers greatly reduced the viscosity of the oligomers and increased the photopolymerization rates of the resins. The flame retardancy and thermal degradation behavior of the UV‐cured films were investigated with the limiting oxygen index (LOI) and thermogravimetric analysis. The results showed that the thermal stability at high temperatures greater than 400°C and the LOI values of the UV‐cured resins, especially those containing epoxy acrylate, were largely improved by the addition of the monomers. The dynamic mechanical thermal properties of the UV‐cured films were also measured. The results showed that the crosslink density increased along with the concentrations of the monomers. However, the glass‐transition temperature decreased with an increasing concentration of DAEEP because of the reduction in the rigidity of the cured films, whereas the glass‐transition temperature increased with the concentration of TAEP because of the higher crosslink density of the cured films. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 185–194, 2005     

Termites as human foods—A comprehensive review

Global food production is anticipated to rise along with the growth of the global population. As a result, creative solutions must be devised to ensure that everyone has access to nutritious, affordable, and safe food. Consequently, including insects in diets has the potential to improve global food and nutrition security. This paper aims to share recent findings by covering edible termites as the main aspect, from their consumption record until consumer acceptance. A total of 53 termite species are reported as edible ones and distributed in 6 biogeographic realms. Generally, termites have a nutrient composition that is suitable for human consumption, and cooked termites are a better dietary choice than their raw counterparts. Besides, increasing customer interest in eating termite-based food can be achieved by making it more palatable and tastier through various cooking processes, that is, boiling, frying, grilling, roasting, smoking, and sun-drying. Moreover, edible termites can also be used as a new source of medication by exhibiting antimicrobial activity. Regarding their advantages, it is strongly encouraged to implement a seminatural rearing system to sustain the supply of edible termites. Overall, this paper makes it evident that termites are an important natural resource for food or medicine. Hence, the long-term objective is to stimulate scientific inquiry into the potential of edible insects as an answer to the problem of global food security.     

Blockchain and IIoT Enabled Solution for Social Distancing and Isolation Management to Prevent Pandemics

Pandemics have always been a nightmare for humanity, especially in developing countries. Forced lockdowns are considered one of the effective ways to deal with spreading such pandemics. Still, developing countries cannot afford such solutions because these may severely damage the country’s economy. Therefore, this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations smoothly. The novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things (IIoT) and blockchain-enabled technologies. Compared to existing studies, the immutable and tamper-proof contact tracing and quarantine management solution is proposed. The use of advanced technologies and information security is a critical area for practitioners in the internet of things (IoT) and corresponding solutions. Therefore, this study also emphasizes information security, end-to-end solution, and experimental results. Firstly, a wearable wristband is proposed, incorporating 4G-enabled ultra-wideband (UWB) technology for smart contact tracing mechanisms in industries to comply with standard operating procedures outlined by the world health organization (WHO). Secondly, distributed ledger technology (DLT) omits the centralized dependency for transmitting contact tracing data. Thirdly, a privacy-preserving tracing mechanism is discussed using a public/private key cryptography-based authentication mechanism. Lastly, based on geofencing techniques, blockchain-enabled machine-to-machine (M2M) technology is proposed for quarantine management. The step-by-step methodology and test results are proposed to ensure contact tracing and quarantine management. Unlike existing research studies, the security aspect is also considered in the realm of blockchain. The practical implementation of the proposed solution also obtains the results. The results indicate the successful implementation of blockchain-enabled contact tracing and isolation management using IoT and geo-fencing techniques, which could help battle pandemic situations. Researchers can also consider the 5G-enabled narrowband internet of things (NB-IoT) technologies to implement contact tracing solutions.     

Stochastic Investigations for the Fractional Vector-Host Diseased Based Saturated Function of Treatment Model

The goal of this research is to introduce the simulation studies of the vector-host disease nonlinear system (VHDNS) along with the numerical treatment of artificial neural networks (ANNs) techniques supported by Levenberg-Marquardt backpropagation (LMQBP), known as ANNs-LMQBP. This mechanism is physically appropriate, where the number of infected people is increasing along with the limited health services. Furthermore, the biological effects have fading memories and exhibit transition behavior. Initially, the model is developed by considering the two and three categories for the humans and the vector species. The VHDNS is constructed with five classes, susceptible humans , infected humans , recovered humans , infected vectors , and susceptible vector based system of the fractional-order nonlinear ordinary differential equations. To solve the number of variations of the VHDNS, the numerical simulations are performed using the stochastic ANNs-LMQBP. The achieved numerical solutions for solving the VHDNS using the stochastic ANNs-LMQBP have been described for training, verifying, and testing data to decrease the mean square error (MSE). An extensive analysis is provided using the correlation studies, MSE, error histograms (EHs), state transitions (STs), and regression to observe the accuracy, efficiency, expertise, and aptitude of the computing ANNs-LMQBP.     

Effects of Dissimilar Curing Systems on the Strength and Durability of Recycled PET-Modified Concrete

Silicon - Since curing remains an essential parameter that directly influences concrete strength and durability, this research aimed at evaluating the effects of water, sodium chloride (NaCl), and...     

Numerical Procedure for Fractional HBV Infection with Impact of Antibody Immune

The current investigations are presented to solve the fractional order HBV differential infection system (FO-HBV-DIS) with the response of antibody immune using the optimization based stochastic schemes of the Levenberg-Marquardt backpropagation (LMB) neural networks (NNs), i.e., LMBNNs. The FO-HBV-DIS with the response of antibody immune is categorized into five dynamics, healthy hepatocytes (H), capsids (D), infected hepatocytes (I), free virus (V) and antibodies (W). The investigations for three different FO variants have been tested numerically to solve the nonlinear FO-HBV-DIS. The data magnitudes are implemented 75% for training, 10% for certification and 15% for testing to solve the FO-HBV-DIS with the response of antibody immune. The numerical observations are achieved using the stochastic LMBNNs procedures for soling the FO-HBV-DIS with the response of antibody immune and comparison of the results is presented through the database Adams-Bashforth-Moulton approach. To authenticate the validity, competence, consistency, capability and exactness of the LMBNNs, the numerical presentations using the mean square error (MSE), error histograms (EHs), state transitions (STs), correlation and regression are accomplished.     

Aspect Level Songs Rating Based Upon Reviews in English

With the advancements in internet facilities, people are more inclined towards the use of online services. The service providers shelve their items for e-users. These users post their feedbacks, reviews, ratings, etc. after the use of the item. The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items. Sentiment Analysis (SA) is a technique that performs such decision analysis. This research targets the ranking and rating through sentiment analysis of these reviews, on different aspects. As a case study, Songs are opted to design and test the decision model. Different aspects of songs namely music, lyrics, song, voice and video are picked. For the reason, reviews of 20 songs are scraped from YouTube, pre-processed and formed a dataset. Different machine learning algorithms—Naïve Bayes (NB), Gradient Boost Tree, Logistic Regression LR, K-Nearest Neighbors (KNN) and Artificial Neural Network (ANN) are applied. ANN performed the best with 74.99% accuracy. Results are validated using K-Fold.     

Vertical Pod Autoscaling in Kubernetes for Elastic Container CollaborativeFramework

Kubernetes is an open-source container management tool which automates container deployment, container load balancing and container(de)scaling, including Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA). HPA enables flawless operation, interactively scaling the number of resource units, or pods, without downtime. Default Resource Metrics, such as CPU and memory use of host machines and pods, are monitored by Kubernetes. Cloud Computing has emerged as a platform for individuals beside the corporate sector. It provides cost-effective infrastructure, platform and software services in a shared environment. On the other hand, the emergence of industry 4.0 brought new challenges for the adaptability and infusion of cloud computing. As the global work environment is adapting constituents of industry 4.0 in terms of robotics, artificial intelligence and IoT devices, it is becoming eminent that one emerging challenge is collaborative schematics. Provision of such autonomous mechanism that can develop, manage and operationalize digital resources like CoBots to perform tasks in a distributed and collaborative cloud environment for optimized utilization of resources, ensuring schedule completion. Collaborative schematics are also linked with Bigdata management produced by large scale industry 4.0 setups. Different use cases and simulation results showed a significant improvement in Pod CPU utilization, latency, and throughput over Kubernetes environment.